SUBSTANTIAL CLINICAL BENEFIT OF COMMON OUTCOME MEASURES FOLLOWING SHOULDER ARTHROPLASTY
Bibliographic record
Abstract
Background and aims: Advanced osteoarthritis of the shoulder joint is associated with significant pain and disability. There is minimal information on substantial clinical benefit (SCB) and responsiveness of the American Shoulder and Elbow Surgery (ASES) score, the relative Constant Murley score (CMS) and the Western Ontario Osteoarthritis of the Shoulder (WOOS) index following shoulder arthroplasty. The purpose of this study was to examine the SCB and responsiveness of these three outcome measures based on patientu2019s report of change at six months and two years following surgery. Methods: Methods: The SCB and responsiveness were calculated based on external anchors related to change in pain, range of motion (ROM) and ability to carry out activities of daily living (ADL). The areas under curve (AUCs) represented responsiveness. Results: The data of 159 and 131 patients with complete follow-up at six and two years were reviewed. The SCB for pain at 6 months varied from 29.1-39.5 and increased to 48.9-53.3 at 2 years. A similar pattern of increased SCB values was observed for ROM and ADL for all measures over time. Responsiveness of all measures was high (AUCs >0.80) at 6 months and further improved at two years (AUCs >0.86). There were no statistically significant differences between the AUC values of the ASES and CMS when compared with the WOOS (P>0.05). Conclusion: The lack of a difference in responsiveness between the joint-specific outcomes and a diseases-specific measure demonstrates equivalence, as opposed to superiority of the WOOS over the ASES and CMS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".